Cross-Domain Generalization

Follow this topic Ask about this topic

Momentum

11 papers in the last four weeks, up 267% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 108

All topics

Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts
May 26, 2026Changhao Miao, Yuntian Zhang, Tongyu Wu +2Reinforcement Learning Adaptive Model Routing
State Key Laboratory of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China · Department of Computer, Control and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, 00185, Italy · School of AI, Beijing Institute of Technology, Beijing 100081, China
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
May 26, 2026Yusuf Brima, Marcellin Atemkeng, Lansana Hassim Kallon +4Tabular Foundation Models Few-Shot Learning
Computer Vision, Institute of Cognitive Science, Osnabrück University, Germany · Department of Mathematics, Rhodes University, South Africa · National Institute for Theoretical and computational Sciences (NITheCS), Stellenbosch, 7600, South Africa +6
MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training
May 25, 2026Ziyu Zheng, Yaming Yang, Ziyu Guan +2Cross-Domain Generalization Cross-Domain Transfer Learning
School of Computer Science and Technology, Xidian University, Xi’an, China · School of Artificial Intelligence, Xidian University, Xi’an, China
Abduction-Deduction Entanglement: Domain Generalization via Representation Transplants
May 24, 2026Kasra Jalaldoust, Elias BareinboumDomain Generalization OOD Generalization
Department of Computer Science Columbia University New York, NY 10027, USA
Cross-Domain Generalization Limits of Vision Foundation Models in Facial Deepfake Detection
May 24, 2026Ibrahim DelibasogluVision Foundation Models Cross-Domain Generalization
Department of Software Engineering, Faculty of Computer and Information Sciences, Sakarya University, Esentepe, Sakarya, 54050 Türkiye.
GenHAR: Generalizing Cross-domain Human Activity Recognition for Last-mile Delivery
May 21, 2026Zhiqing Hong, Zelong Li, Xiubin Fan +5Human Activity Recognition Domain Generalization
HKUST (GZ) Guangzhou, China · JD Logistics Beijing, China · Beijing Normal–Hong Kong Baptist University Zhuhai, China +2
A Systematic Failure Analysis of Vision Foundation Models for Open Set Iris Presentation Attack Detection
May 18, 2026Rahul Anand, Siddharth Singh, Dileep A D +2Vision Foundation Models Open-Set Recognition
Indian Institute of Technology, Dharwad, India. · SAFE Center, Norwegian University of Science and Technology (NTNU), Norway. · Indian Institute of Information Technology Dharwad, India.
Domain Incremental Learning for Pandemic-Resilient Chest X-Ray Analysis
May 18, 2026Danu KimChest X-Ray Classification Medical Diagnosis
Korea International School, Jeju Campus, Jeju-do 63644, Republic of Korea
Continual Learning of Domain-Invariant Representations
May 15, 2026Pascal Janetzky, Tobias Schlagenhauf, Stefan FeuerriegelOOD Generalization Cross-Domain Generalization
LMU Munich, Munich, Germany · Munich Center for Machine Learning, Munich, Germany · Bosch Center for Artificial Intelligence, Renningen, Germany +1
UFO: A Domain-Unification-Free Operator Framework for Generalized Operator Learning
May 12, 2026Hanli Qiao, George Em Karniadakis, Muhammad MuniruzzamanCross-Domain Generalization PDE Operator Learning
Water and Mining Environment Unit, Geological Survey of Finland, Vuorimiehentie 5, Espoo, 02151, Finland · Division of Applied Mathematics, Brown University, 170 Hope Street, Providence, RI 02912, USA · Institute of Geosciences, University of Bonn, Kirschallee 1-3, Bonn, 53115, Germany
How Useful Is Cross-Domain Generalization for Training LLM Monitors?
May 12, 2026Sam Martin, Fabien RogerSupervised Fine-Tuning Cross-Domain Generalization
Anthropic Fellows Program · Anthropic
Cross-Modal-Domain Generalization Through Semantically Aligned Discrete Representations
May 12, 2026Souptik Sen, Raneen Younis, Zahra AhmadiCross-Modal Learning Representation Learning
Peter L. Reichertz Institute for Medical Informatics, Hannover Medical School, Germany · Lower Saxony Center for AI and Causal Methods in Medicine (CAIMed), Hannover, Germany
More Than Meets the Eye: A Semantics-Aware Traffic Augmentation Framework for Generalizable Website Fingerprinting
May 12, 2026Youquan Xian, Xueying Zeng, Lingjia Meng +6Synthetic Data Augmentation Cross-Domain Generalization
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China · School of Computer Science and Engineering, Beihang University, Beijing, China · Zhongguancun Laboratory, Beijing, China +2
One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
May 10, 2026Bowen He, Juncheng Dong, Lin Lin +1Reinforcement Learning Transformer
Duke University, Durham, U.S.A.
Diagnosing and Mitigating Domain Shift in Permission-Based Android Malware Detection
May 9, 2026Md Rafid IslamAndroid Malware Detection Cross-Domain Generalization
North South University, Department of Electrical and Computer Engineering, Bashundhara, Dhaka, 1229, Bangladesh
Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning
May 9, 2026Zhen-Hao Xie, Yan Wang, Hao Sun +3Class-Incremental Learning Continual Learning
School of Artificial Intelligence and the State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, China
Flatness and Gradient Alignment Are Both Necessary: Spectral-Aware Gradient-Aligned Exploration for Multi-Distribution Learning
May 8, 2026Aristotelis Ballas, Christos DiouSharpness-Aware Minimization Multi-Task Learning
Department of Informatics and Telematics Harokopio University of Athens Omirou 9, Athens, Greece
On the Invariance and Generality of Neural Scaling Laws
May 8, 2026Xing Han, Liu Ziyin, Suchi Saria +1Language Model Scaling Laws Cross-Domain Generalization
Johns Hopkins University Baltimore, MD 21218, USA · NTT Research, MIT Cambridge, MA 02139, USA · Johns Hopkins University, Bayesian Health Baltimore, MD 21218, USA +1
HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning
May 7, 2026Yu Feng, Zhen Tian, Haoran Luo +8Prompt Learning Domain-Incremental Learning
China Mobile Research Institute, China · Beijing University of Posts and Telecommunications, China · Nanyang Technological University, Singapore +1
Feature-Augmented Transformers for Robust AI-Text Detection Across Domains and Generators
May 5, 2026Mohamed Mady, Johannes Reschke, Björn SchullerAI-Generated Text Detection Transformer
Chair of Health Informatics, Technical University of Munich (TUM), Germany · OTH Regensburg, Germany · GLAM – Group on Language, Audio & Music, Imperial College London, United Kingdom
ReLeaf: Benchmarking Leaf Segmentation across Domains and Species
May 5, 2026Robert Martinko, Daniel Steininger, Julia Simon +2Agricultural Image Analysis Instance Segmentation
1AIT Austrian Institute of Technology, Center for Vision, Automation & Control · University of Applied Sciences Technikum Wien, Computer Science & Applied Mathematics
Geometry over Density: Few-Shot Cross-Domain OOD Detection
May 5, 2026Shawn Li, You Qin, Jiate Li +4Diffusion-Based OOD Detection Distribution Shift Detection
University of Southern California · National University of Singapore · Amazon
Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification
May 4, 2026Shubham Harkare, Arvind Yogesh Suresh Babu, Yash KulkarniGradient-Based Attribution Sentiment Analysis
University of Michigan
Evaluating Tabular Representation Learning for Network Intrusion Detection
May 4, 2026Muhammad Usman Butt, Andreas Hotho, Daniel SchlörRepresentation Learning Network Intrusion Detection
Julius-Maximilians-Universität Würzburg Würzburg, Germany · Data Science Chair Center for Artificial Intelligence and Data Science Julius-Maximilians-Universität Würzburg Würzburg, Germany
MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
May 3, 2026Yavuz Yarici, Ghassan AlRegibDomain Generalization Cross-Domain Generalization
1OLIVES at the Center for Signal and Information Processing CSIP, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization
May 1, 2026Zoe Fowler, Ghassan AlRegibFederated Learning Aggregation Cross-Domain Generalization
Georgia Institute of Technology
AIDA-ReID: Adaptive Intermediate Domain Adaptation for Generalizable and Source-Free Person Re-Identification
Apr 30, 2026Sundas Iqbal, Qing Tian, Danish Ali +2Multi-Source Domain Adaptation Source-Free Domain Adaptation
School of Software, Nanjing University of Information Science and Technology, Nanjing 210044, China · Wuxi Institute of Technology, Nanjing University of Information Science and Technology, Wuxi 214000, China · School of Computer Science, Wuhan University, Wuhan 430070, China +2
Dreaming Across Towns: Semantic Rollout and Town-Adversarial Regularization for Zero-Shot Held-Out-Town Fixed-Route Driving in CARLA
Apr 30, 2026Feeza Khan Khanzada, Jaerock KwonDomain Generalization Cross-Domain Generalization
Department of Electrical and Computer Engineering, University of Michigan–Dearborn, Dearborn, MI 48128 USA
Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods
Apr 29, 2026Taida Li, Yujun Yan, Fei Dou +2Cross-Subject EEG Decoding EEG Decoding
Department of Computer Science, University of North Carolina at Charlotte, Charlotte, United States · Department of Computer Science, Dartmouth College, Hanover, United States · School of Computing, University of Georgia, Athens, United States +1
Bridge: Basis-Driven Causal Inference Marries VFMs for Domain Generalization
Apr 29, 2026Mingbo Hong, Feng Liu, Caroline Gevaert +2Domain Generalization Cross-Domain Generalization
University of Twente · 2Drexel University

May 26, 2026, cs.LGJ/K move · Enter open · S save

Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts

Changhao Miao, Yuntian Zhang, Tongyu Wu, Fang Deng+1

State Key Laboratory of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China · Department of Computer, Control and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, 00185, Italy · School of AI, Beijing Institute of Technology, Beijing 100081, China

Reinforcement Learning Adaptive Model Routing Vehicle Routing Cross-Domain Generalization Mixture-of-Experts Models RL for Combinatorial Optimization

Open paper AskPDF arXiv

In recent years, Deep Reinforcement Learning (DRL) has achieved substantial progress on Vehicle Routing Problems (VRPs). However, existing DRL-based methods are typically trained on instances generated from a uniform distribution, which limits their performance under real-world distribution shifts. In this paper, we aim to develop a generalization-oriented model that partitions the policy network into multiple modules and adaptively recombines modules to form specific policies during inference. Specifically, we propose Residual Refined Experts with Instance-level Gating (R2E-IG) to improve cross-distribution generalization. Our contributions are threefold: (1) We introduce a Residual Refined Expert (R2E) architecture that enhance expert expressiveness via residual refinement; (2) We design an instance-level gating mechanism that learns distribution-aware instance representations and routes inputs to suitable modules; (3) We propose a mixed-distribution training mechanism equipped with Dynamic Weight Adaption (DWA), which dynamically reweights training data from different distributions to emphasize more informative ones. Extensive experiments show that R2E-IG achieves competitive performance against state-of-the-art baselines on both in-distribution and out-of-distribution instances across synthetic and benchmark datasets. Moreover, R2E-IG is generic and can be easily integrated into existing DRL-based methods to further improve performance.

Momentum

Related topics

Latest papers 108